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  Published Paper Details:

  Paper Title

DYNAMIC PRICING USING MACHINE LEARNING

  Authors

  Shaikh Kaneez Fatima,  Ansari Urufa Najeeb,  Rumani Shagufi,  Waheeda Dhokley,  Sayyed Mohd Amin

  Keywords

Dynamic pricing, Demand forecasting, Revenue generation,Rating prediction

  Abstract


This project aims to implement a Dynamic pricing system that automatically fluctuates the price of the assets based on data about supply, demand, ratings, amenities, seasonality, ease of transit, and the rates that have been set by based on market competitions and creates different prices for different customers. This System focuses on increasing the revenue of the owner of the asset. The owner of the Assets generates revenue by giving their assets on rent. Assets here, in this case, are rented by the customer on an hourly basis. Dynamic pricing will be helping the owners in increasing the revenue by setting the prices appropriately based on demand and supply, ratings, seasonality. Sales trends, and peak sales hours would also be factors that would be considered in calculating the dynamic pricing. This will help the owners of the assets to get more profit. Dynamic pricing helps the owners of the assets to get more bookings and can get more profit, and smartly rent their assets at good rates.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2006263

  Paper ID - 195134

  Page Number(s) - 1934-1937

  Pubished in - Volume 8 | Issue 6 | June 2020

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Shaikh Kaneez Fatima,  Ansari Urufa Najeeb,  Rumani Shagufi,  Waheeda Dhokley,  Sayyed Mohd Amin,   "DYNAMIC PRICING USING MACHINE LEARNING", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.8, Issue 6, pp.1934-1937, June 2020, Available at :http://www.ijcrt.org/papers/IJCRT2006263.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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